Bassist: A Tool for MCMC Simulation of Statistical Models

Bassist is a tool that automates the use of
hierarchical Bayesian models in complex analysis tasks.
Such models offer a powerful framework for modeling statistically
complex real-world phenomena. So far, the lack of computational tools has
hindered the practical use of hierarchical Bayesian models.

Bayesian models are specified to Bassist in terms of its high-level language.
Given a model specification, Bassist generates a model-specific
program for the analysis of data files. The generated program applies
MCMC (Markov chain Monte Carlo) approximation, in particular the
Metropolis-Hastings method, to obtain a sample from the posterior
distribution of the parameters and missing data.

Bassist is not actively developed and maintained anymore.
Some problems in compiling the source code with newer versions
of compilers are anticipated. Unfortunately we don't have the
resources to actively support users.
(In an absolute emergency, you can direct technical questions to
Jouni Seppänen.)